1. Field of the Invention
The present invention relates to artificial or computer vision systems, e.g. vehicular vision systems such as those used in collision avoidance systems. In particular, this invention relates to a method and apparatus for detecting and removing the ground from scene images.
2. Description of the Related Art
Collision avoidance systems utilize some type of a sensor system to detect objects in front of an automobile or other form of a platform. Some prior art sensor systems have used radar and/or infrared sensors to generate rudimentary images of scenes in front of a vehicle. By processing that imagery, objects can be detected.
Recently, stereo cameras sensor systems that process 2-D camera images into a depth map have become of interest. By comparing pre-rendered 3-D vehicle templates against the depth map objects can be identified. In such systems the pitch angle of the stereo cameras relative to the ground plane is critical. This is because vertical positions in the depth map are largely determined by the camera pitch angle. If the camera pitch angle is incorrect, such as when the pitch angle changes due to vehicle dynamics (e.g., hitting a pothole), the pre-rendered templates match incorrectly with the depth map. This can result in either false positives (typically, attempting to match too low, i.e. into the ground) or false negatives (typically, attempting to match too high, i.e. into the sky).
Another problem can result if the stereo camera-to-ground plane calibration is accurate, but the host vehicle is approaching a slope, hill or even a bump in the road. Then, the calibration ground plane does not match the road surface ground plane. In such cases the camera-to-ground plane calibration can be dynamically adjusted to compensate for the difference, eliminating false positives and false negatives. In the case of an embankment or other impassable obstruction, there is no need to attempt to match vehicle templates against the road surface. Doing so is computationally inefficient and may create false positives.
Therefore, a vision system that detects the ground would be useful. Also useful would be a vision system that detects the ground and that compensates for differences between the actual ground plane and the assumed (or calibrated) depth map ground plane. A vision system that detects the ground and that removes the ground from the depth map would also be useful, since the ground is usually not considered a threatening object.